It looks like some details about the next AIY Projects kit could be announced in the next issue of the Magpi according to page 70 of the Hackspace magazine. Looks like the AIY Projects Vision Kit is next. Can't wait!

Last edited by KanoMaster22 on Sun Nov 26, 2017 8:51 pm, edited 1 time in total.

I am not sure "Incoming!" is an announcement of a free camera or whatever with the MagPi, but I guess we can look forward to them being hoovered up from shops by ebay scalpers and the lucky few if it is. The moral is; get a subscription if you don't want to miss out on any MagPi freebies.

Google mentioned AIY vision and motion detection back in August but I haven't seen any details of what that actually provides for. I was expecting the next giveaway to be servos or something which would attach to the existing voice kit.

I expect it means it is coming soon and that it will be announced in the next issue of the Magpi (maybe not build details until the next issue). It may not come in the form of a free kit or a kit that can be bought and would make sense for it to be based on the already existing Raspberry Pi Camera Module. All of this is just a guess apart from the bit that AIY Projects Vision Kit is 'incoming'. By the fact that the AIY Projects Vision is the main thing on the front cover, I am guessing it may be one or two months until the actual kit is released. For those who can't be bothered find the page in Hackspace see the image attached.

I've just received my Magpi and checked out the kit on the Microcenter website. They are taking pre-orders but the killer is that the kit will only be available as a store pickup. This effectively means that only American buyers will be able to buy one.

I know! The aim of AIY Projects is to make AI accessible to makers but this is the complete opposite! It is near impossible to get the new kit! Even if you live in the country it is supposed to be available. It completely impossible to get in the UK until Easter time!

Let's say the RPi3 can do detection at 0.5 fps, if this add-on board is 60x faster than means 30 fps and we have a full real-time detector, presumably with a lot lower power than the big Nvidia GPU you'd otherwise need, since I don't see a heatsink on that chip. Is is true?

Apart from the speed, how does it work in practice? Ideally I'd want the chip to be passing me the bounding box of the detected objects from the real-time video stream, tied to each frame where an object is detected. Does the camera connect to the board, or the Pi, or both? Seems like you need video-rate communication from the board to the Pi, which can't happen just over the GPIO, unless the board acts as a video splitter so both board and RPi get the video feed (?) Even in that case, how do you match up frames because there is significant and perhaps variable latency between the MIPI video data going into the Pi's GPU, and "real-time" communication through any other interfaces.

I know! The aim of AIY Projects is to make AI accessible to makers but this is the complete opposite! It is near impossible to get the new kit! Even if you live in the country it is supposed to be available. It completely impossible to get in the UK until Easter time!

The release of the AIY Vision is designed for the Zero and all announcement were referenced with the Zero.
There was never a mention of which Pi it was faster with, I like everyone also assumed it was compared to the Zero.

In the deep learning literature I've read, the standard performance metric is frames per second, along with a Precision-Recall curve, and mean Average Precision. I've seen three specific networks mentioned with the AIY Project (person/dog/cat, facial expression/sentiment, categorize 1001 object types). If these are running now on the hardware, I assume they know what FPS values they achieve, so I look forward to seeing that information at some point.

By the way, I have to say the full (not "tiny") YOLO network is pretty impressive, although very slow using only a CPU, not GPU. I'm using https://github.com/thtrieu/darkflow and here is an example of it correctly detecting four cars (some only partially visible) and most impressively the driver in the PERSON category, even with the eyes obscured by the rearview mirror and not a lot else visible. This image was captured by PiKrellCam, before being fed into the network.